资源列表
optLib
- 提供了常用的优化算法,包括约束变尺度法,拟牛顿法,遗传算法,多目标优化算法,Hookjeeves算法等多种算法。使用时先写好优化模型,生成相应的dll此优化库可以根据选择的算法对优化模型进行优化求解。-provide a common method of optimization, including CVMO1-, quasi-Newton method, genetic algorithm, multi-objective optimization algorithm, Hookjeeves
facerecognisionmatlabcode
- 人脸识别MATLAB源代码,与大家共分享。-face recognition MATLAB source code, and everyone has to share.
gdfhgdfhgd
- feret人脸图象数据库处理代码,与大家共享-feret facial image database handling code, and share
02092028
- 1. 背景简介 日常生活中经常有自动售货机,这种机器不需要人来随时控制,只是按照其内部的一些默认程序来 工作,是一种比较简单的人工智能程序,本程序为对这种机器的一种模拟。 2.项目目标 (1)向顾客显示所售的各种商品; (2)让顾客进行选择; (3)向顾客显示所选商品的价格; (4)收款; (5)发送顾客所选择的商品; (6)向顾客找零。 3.运行环境 PⅢ级别计算机(CPU主频300Mhz以上、128MB内存) WINDOWS操作系统
6117519351200615205357358327
- 可用的SOM_Algorithm-available SOM_Algorithm
BPfile
- 这是个可执行文件,源代码在博客可以找到 http://sillyfox.ygblog.com/user1/24279/default.html-This is executable files, the source code can be found at http blog : / / sillyfox.ygblog.com/user1/24279/defaul t.html
0~9bp_test
- 编程环境为matlab 该程序实现在已经训练好的神经网络的情况下,实现对数字的识别任务.-Matlab programming environment for the realization of the program has trained neural network circumstances, Implementation of digital identification tasks.
SGA_MATLAB
- 用matlab自编写的简单遗传算法程序(SGA) -using Matlab since the preparation of a simple genetic algorithm (SGA)
SGA_AUTO.C
- 自适应遗传算法之C语言版本,自适应遗传算法之C语言版本-adaptive Genetic Algorithms C language version, adaptive Genetic Algorithms in C Language Version
GATBX_xiugaiban
- 英国设菲尔德大学开发的遗传算法工具箱以及雷英杰老师编写的<<matlab遗传算法工具箱及其应用>>中的例子源程序,对一些错误进行了修改,并调试成功.-Britain developed at the University of Sheffield, the genetic algorithm toolbox and Lei Yingjie prepared by the teacher
QuantumGeneticAlgorithm
- 量子遗传算法并行性好,不易陷入早熟,是目前在遗传算法方面一个比较新研究,该压缩包里包含了大量了一些优秀的量子遗传算法的一些优秀文章.-quantum parallelism of genetic algorithms, and not caught early, which is the genetic algorithm in a relatively new area, The compressed bundle contains a number of outstanding Quantu
my_sga
- 有用的SGA的Matlab源代码,求函数的最大值,根据SGA的C代码改变,很容易懂,对SGA 学习很有帮助-useful SGA Matlab source code, the maximum demand function, According to the SGA C code change, it is easy to understand and very helpful to SGA